Purpose

The purpose of this paper is to identify the drivers of residential price as well as the degree co-movement of housing among different states in Malaysia.

Design/methodology/approach

This study adopted an advanced econometrics technique: the dynamic autoregressive-distributed lag (DARDL) and – the time-frequency domain approach known as the wavelet coherence test. The DARDL model was applied to identify the cointegrating relationships and the CWT was used to analyze the co-movement and lead–lag relationships among four states’ regional housing prices. The extracted data were mainly on annual basis and comprised macroeconomics and financial factors. Information with regard to residential prices and other variables was extracted from the National Property Information Centre (NAPIC) website, the Central Bank of Malaysia Statistics Report, the Department of Statistics, Malaysia, I-Property.com and the World Bank (WB). The data covered in this study were the pool data from four main states in Malaysia and different categories of residential properties.

Findings

The empirical results indicate that there were long-run cointegration relationships between the housing price and capital gain and loss, rental per square feet, disposable income, inflation, number of marriages, deposit rate, risk premium and loan-to-value (LTV) ratio. While the wavelet analysis shows that (1) in the long run, Kuala Lumpur housing price having strong co-movement with Selangor, Penang and Melaka housing prices except for Johor and (2) the lead–lag relationship also postulates Kuala Lumpur housing price having in-phase category with Selangor, Penang and Melaka housing prices except for Johor.

Practical implications

This study offers relevant practical implications. First, the study proposes an active collaboration between the private sector and government support which may help to smooth the pricing issue of residential properties. More low-cost residential projects are needed for focus groups including middle- and low-income earners. Furthermore, the results are expected to provide real estate investor in Malaysia, an improved understanding of the regional housing market price dynamics.

Originality/value

The findings of this study were obtained from various reliable sources; therefore, the results reflected the analysis of price drivers and co-movements. Furthermore, findings from this study lend some support to the argument on the rise of residential prices and offer several policy implications from a practical point of view with regard to the residential market.

中文翻译：

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马来西亚的住宅房地产市场：价格驱动因素和共同运动分析

目的

本文的目的是确定马来西亚不同州之间的住宅价格驱动因素以及住房的联动程度。

设计/方法/方法

这项研究采用了先进的计量经济学技术：动态自回归分布滞后（DARDL）和–时频域方法，即小波相干检验。DARDL模型用于识别协整关系，而CWT用于分析四个州的区域房价之间的联动关系和超前滞后关系。提取的数据主要基于年度数据，包括宏观经济和财务因素。有关房屋价格和其他变量的信息摘自国家财产信息中心（NAPIC）网站，马来西亚中央银行统计报告，马来西亚统计局，I-Property.com和世界银行（WB）。

发现

实证结果表明，房价与资本损益，每平方英尺租金，可支配收入，通货膨胀，结婚人数，存款率，风险溢价和贷款价值之间存在长期协整关系。比率。小波分析表明，（1）从长远来看，吉隆坡的房价与雪兰莪，槟城和马六甲的房价有很强的联动性，柔佛州除外；（2）领先与滞后的关系也假定吉隆坡房价具有与雪兰莪，槟城和马六甲的房价分阶段划分，柔佛州除外。

实际影响

这项研究提供了相关的实际意义。首先，该研究提出了私营部门与政府支持之间的积极合作，这可能有助于缓解住宅物业的定价问题。包括中低收入者在内的焦点小组需要更多的低成本住宅项目。此外，该结果有望为马来西亚的房地产投资者提供对区域住房市场价格动态的更好理解。

创意/价值

这项研究的发现是从各种可靠的来源获得的。因此，结果反映了对价格动因和共同运动的分析。此外，这项研究的结果为住宅价格上涨的论点提供了一定的支持，并从实践的角度对住宅市场提出了一些政策含义。